U.S. patent application number 10/880650 was filed with the patent office on 2005-03-03 for mobile ipv6 network having multiple home agents and method of load balance.
Invention is credited to Deng, Hui, Huang, Xiao Long, Niu, Zhisheng, Tanabe, Shiro, Zhang, Kai.
Application Number | 20050047420 10/880650 |
Document ID | / |
Family ID | 34155922 |
Filed Date | 2005-03-03 |
United States Patent
Application |
20050047420 |
Kind Code |
A1 |
Tanabe, Shiro ; et
al. |
March 3, 2005 |
Mobile IPv6 network having multiple home agents and method of load
balance
Abstract
In a mobile IPv6 network having multiple distributed regression
home agents and a load balance method for the multiple regression
home agents, the network comprises a plurality of mobile subnets
connected to each other through an Internet. Each mobile subnet
comprises an access router, a plurality of mobile nodes, and a
plurality of regression agents. The regression agents are arranged
in a distributed topology structure. The regression agents exchange
information with each other by performing a broadcast of traffic
load information (table) among the regression agents. Further, each
of the regression agents has a traffic load table to perform the
load balance operation accordingly.
Inventors: |
Tanabe, Shiro; (Hidaka,
JP) ; Huang, Xiao Long; (Beijing, CN) ; Deng,
Hui; (Beijing, CN) ; Zhang, Kai; (Beijing,
CN) ; Niu, Zhisheng; (Beijing, CN) |
Correspondence
Address: |
ANTONELLI, TERRY, STOUT & KRAUS, LLP
1300 NORTH SEVENTEENTH STREET
SUITE 1800
ARLINGTON
VA
22209-9889
US
|
Family ID: |
34155922 |
Appl. No.: |
10/880650 |
Filed: |
July 1, 2004 |
Current U.S.
Class: |
370/395.52 |
Current CPC
Class: |
H04L 67/1002 20130101;
H04W 8/12 20130101; H04W 80/04 20130101 |
Class at
Publication: |
370/395.52 |
International
Class: |
H04L 012/56 |
Foreign Application Data
Date |
Code |
Application Number |
Jul 1, 2003 |
CN |
03145741.X |
Claims
What is claimed is:
1. A mobile IPv6 network having multiple distributed regression
home agents, which includes a plurality of mobile subnets and an
Internet, the mobile subnets being connected to each other through
the Internet, the mobile Ipv6 network comprising: each mobile
subnet including an access router, a plurality of mobile nodes and
a plurality of regression agents; the regression agents arranged in
a distributed topology structure; the regression agents exchanging
information with each other by performing a broadcast of traffic
load information (table) among the regression agents; and the
regression agents each having a traffic load table to perform a
load balance operation accordingly.
2. The mobile IPv6 network having multiple distributed regression
home agents according to claim 1, wherein the traffic load table
records a traffic load level of all the regression agents, and
comprises information of a regression agent address, a traffic
load, and a registered mobile node number.
3. The mobile IPv6 network having multiple distributed regression
home agents according to claim 1 or 2, wherein each of the
regression agents always monitors its traffic load and registered
mobile node number.
4. The mobile IPv6 network having multiple distributed regression
home agents according to claim 1 or 2, wherein each regression
agent periodically broadcasts the traffic load information to the
other regression agents, and once receiving the traffic load
information broadcasted by the other regression agents, the
regression agent timely updates its traffic load table.
5. The mobile IPv6 network having multiple distributed regression
home agents according to claim 4, wherein, in each regression
agent, when registering a mobile node, a corresponding timer starts
clocking, and a binding time of the current registration is stored
into a update binding buffer, and after the timer exceeds the
binding time, i.e., after the timer of the corresponding mobile
node is time out, a reassignment of the regression agent is
performed to the mobile node.
6. The mobile IPv6 network having multiple distributed regression
home agents according to claim 4, wherein, when the reassignment of
the regression agent is confirmed, by using a dynamic regression
agent address discovery mechanism DHAAD, the regression agent
actively sends an ICMP response information packet to the mobile
node, in which the ICMP response information packet is different
from a standard ICMP response datagram, and this ICMP response
information packet comprises only newly selected regression agent
information, not including table information of the regression
agent.
7. The mobile IPv6 network having multiple distributed regression
home agents according to claim 6, wherein, after the mobile node
receives the ICMP response information packet, the mobile node
compares a new regression agent and its old regression agent, and
if the new regression agent is different from the old regression
agent, the mobile node modifies its regression agent and
simultaneously sends binding update information to the new
regression agent.
8. The mobile IPv6 network having multiple distributed regression
home agents according to claim 6, wherein, according to an IPv6
protocol, the traffic load information of the broadcast is based on
unsolicited router broadcast information in the IETF neighbor
discovery protocol, that is, by setting a new option and a traffic
load, the traffic load information is embedded into an optional
region of the unsolicited router broadcast information.
9. A load balance method for multiple regression home agents,
comprising the steps of: (S1) determining whether a load is larger
than a threshold or not, and executing Step S2 if a determined
result is "YES" and executing Step S3 if the determined result is
"NO"; (S2) determining whether there is a "LIGHT" regression agent
or not, and executing Step S4 if a determined result is "YES" and
executing Step S5 if the determined result is "NO"; (S3)
determining whether the registered mobile node number in all
"LIGHT" regression agents is top 10% or not, and executing Step S8
if a determined result is "YES" and executing Step S7 if the
determined result is "NO"; (S4) randomly selecting one of the
"LIGHT" regression agents and returning; (S5) determining whether
the registered mobile node number in non-"LIGHT" regression agents
is top 10% or not, and executing Step S6 if a determined result is
"YES" and executing Step S7 if the determined result is "NO"; (S6)
randomly selecting one of bottom 10% regression agents in the
non-"LIGHT" regression agents and returning; (S7) performing no
handoff operation of the regression agent and returning; and (S8)
randomly selecting one of bottom 10% regression agents in all the
"LIGHT" regression agents and returning.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] The present application claims priority from Chinese patent
application No. 03145741.X filed on Jul. 1, 2003, the content of
which is hereby incorporated by reference into this
application.
BACKGROUND OF THE INVENTION
[0002] The invention relates in general to a mobile IPv6
communication technology. More specifically, the present invention
relates to a mobile IPv6 network having multiple distributed
regression home agents and a load balance method for the multiple
distributed regression home agents. It mainly uses registered
mobile node information and traffic information in the mobile IPv6
network to share the traffic load of the regression agents.
[0003] Recently, many researches relate to how to combine the
wireless communication and the Internet. The mobile IPv6 standard
(Mobility support in IPv6 <Draft-ietf-mobileip-ipv6-23>,
2003), proposed by D. B. Johnson, C. Perkins and J. Arkko in IETF,
is considered to be an important technology for implementing the
integrated wireless communication and the seamless communication of
a wired network. In the mobile IPv6, when a mobile node is away
from the regression network, there should be a regression agent to
maintain registered information of the mobile node. The regression
agent represents an IP datagram that the mobile node catches and
transmits to the registered mobile node and packs and transmits to
the mobile node. When the number of the mobile nodes serviced by
the regression agent increases significantly, the datagram will be
queued at the regression agent, causing a long delay and a long
registration process. Under a fixed traffic, for example, in the
mobile IPv6 network supporting multimedia applications and having
multiple mobile nodes, since the regression agent has to bear many
packet tunnel datagrams, the regression agent becomes a traffic
bottleneck. In general, the traffic bottleneck causes delays. More
seriously, it causes breakdown of the regression agent.
[0004] In the mobile IPv4 network, there are several methods
proposed to solve the aforementioned problems. However, their
research objects are to use numerical results of their analysis
models, rather than to implement a technology in connection with a
real mobile IPv6. Therefore, they are restricted and limited. At
the same time, these results are not very sensitive to changes of
unimportant parameters. These methods cannot previously prevent the
occurrence of traffic load bottleneck phenomenon.
[0005] All of the aforementioned methods ignore preventing the
occurrence of traffic load bottleneck in advance and how to be
implemented with the IETF (International Engineering Technology
Force) mobile IP standard. Namely, these methods are only analysis
models and away from real situation. Eventually, they seldom
consider the situation of the mobile IPv6.
SUMMARY OF THE INVENTION
[0006] According to the foregoing description, an object of this
invention is to provide an IPv6 network having multiple distributed
regression home agents and a load balance method for the multiple
regression home agents.
[0007] An IPv6 network having multiple distributed regression home
agents according to the present invention, which includes a
plurality of mobile subnets and an Internet, the mobile subnets
being connected to each other through the internet, comprises: each
mobile subnet including an access router, a plurality of mobile
nodes, and a plurality of regression agents; the regression agents
arranged in a distributed topology structure; the regression agents
exchanging information with each other by performing a broadcast of
traffic load information (table) among the regression agents; and
each of the regression agents having a traffic load table to
perform a load balance operation accordingly.
[0008] In the aforementioned mobile IPv6 network having multiple
distributed regression home agents, the traffic load table records
a traffic load level of all regression agents and comprises
information of a regression agent address, a traffic load, and a
registered mobile node number. Each of the regression agents always
monitors its traffic load and registered mobile node number. Each
regression agent periodically broadcasts the traffic load
information to the other regression agents; once receiving the
traffic load information broadcasted by other regression agents,
the regression agent timely updates its traffic load table. In each
regression agent, when registering a mobile node, a corresponding
timer starts clocking and a binding time of the current
registration is stored into a update binding buffer; after the
timer exceeds the binding time, i.e., the timer of the
corresponding mobile node is time out, a reassignment of regression
agent is performed to the mobile node. When the reassignment of
regression agent is confirmed, by using a dynamic regression agent
address discovery mechanism DHAAD, the regression agent actively
sends an ICMP response information packet to the mobile node,
wherein the ICMP response information packet is different from a
standard ICMP response datagram and this ICMP response information
packet can only have newly selected regression agent information,
not including table information of the regression agent. After the
mobile node receives the ICMP response information packet, the
mobile-node compares a new regression agent and its old regression
agent; if the new regression agent is different from the old
regression agent, the mobile node modifies its regression agent and
simultaneously sends binding update information to the new
regression agent. According to an IPv6 protocol, the traffic load
information of the broadcast is based on unsolicited router
broadcast information in the IETF neighbor discovery protocol, that
is, by setting a new option and a traffic load, the traffic load
information is embedded into an optional region of the unsolicited
router broadcast information.
[0009] A load balance method for multiple regression home agents
according to the present invention comprises the steps of: (S1)
determining whether a load is larger than a threshold or not, and
executing Step S2 if a determined result is "YES" and executing
Step S3 if the determined result is "NO"; (S2) determining whether
there is a "LIGHT" regression agent or not; executing Step S4 if a
determined result is "YES" and executing Step S5 if the determined
result is "NO"; (S3) determining whether the registered mobile node
number in all "LIGHT" regression agents is top 10% or not, and
executing Step S8 if a determined result is "YES" and executing
Step S7 if the determined result is "NO", execute Step S7; (S4)
randomly selecting one of the "LIGHT" regression agents and
returning; (S5) determining whether the registered mobile node
number in non-"LIGHT" regression agents is top 10% or not, and
executing Step S6 if a determined result is "YES" and executing
Step S7 if the determined result is "NO"; (S6) randomly selecting
one of bottom 10% regression agents in the non-"LIGHT" regression
agents and returning; (S7) performing no handoff operation of the
regression agent and returning; (S8) randomly selecting one of
bottom 10% regression agents in all "LIGHT" regression agents and
returning.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] FIG. 1 is a schematic diagram showing a mobile IPv6 network
having multiple distributed regression home agents according to the
present invention, in which a triangle routing communication
situation is shown.
[0011] FIG. 2 is a schematic diagram showing a mobile IPv6 network
having multiple distributed regression home agents according to the
present invention, in which a situation of traffic load-broadcast
is performed among the multiple regression home agents.
[0012] FIG. 3 is a diagram showing an example of a distributed
regression agent topology structure and a traffic load table
described in the network of FIG. 2.
[0013] FIG. 4 is a flow chart of a load balance method for multiple
regression home agents according to the present invention.
[0014] FIG. 5 is a simulation result under a test using the load
balance method for multiple regression home agents according to the
present invention.
DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0015] FIG. 1 is a schematic diagram of a mobile IPv6 network
having multiple distributed regression home agents according to the
present invention. In the IPv6 network, a number of mobile subnets
(1, 2 and 3) are connected via the Internet. Assuming the mobile
subnet (1) is a local mobile subnet of a mobile node (8), and the
mobile subnet (1) is a regression network of the mobile node (8).
In general, a mobile subnet comprises an access router, an agent
server, and a number of mobile nodes. According to the mobile IPv6
network of the present invention, each mobile subnet comprises an
access router, a number of agent servers, and a number of mobile
nodes. For example, in the regression network (8), there are many
regression agents (HA1, HA2, . . . n). These regression agents
(HA1, HA2, . . . n) are arranged according to a distributed
topology structure, and are equal to each other. When the mobile
node (8) is just away from the regression network (8), the
communication between a communication node (4) of calling the
mobile node (8) and the mobile node (8) is performed by a triangle
router through the regression network (8).
[0016] FIG. 2 is a schematic diagram showing a mobile IPv6 network
having multiple distributed regression home agents according to the
present invention, and shows a situation of a traffic load
broadcast among the regression agents. Since the aforementioned
regression agents are arranged based on the distributed topology
structure, these regression agents (HA1, HA2, . . . , n) should be
organically connected to form high performance and coordinate
organism in order to reasonably and efficiently distribute loads.
Therefore, the broadcast of the traffic load information (table) is
performed among the regression agents, i.e., information is
exchanged with each other. Each regression agent can balance load
according to the traffic load information.
[0017] In order to obtain and maintain the traffic information,
each regression agent maintains a so-called traffic load table (see
FIG. 3). The traffic load table records traffic levels of all
regression agents.
[0018] FIG. 3 shows an actual example of a traffic load table.
Regression agent IP address information of the regression agent,
load of the regression agent, and number of mobile nodes registered
at the regression agent are regions of the traffic load table. The
table shows the load and the number of the registered mobile nodes
of each regression agent (HA1-HAn) at one particular time.
[0019] Each region of the traffic load table will be described in
detail as follows.
[0020] 1. Agent Address
[0021] The regression agent address is an IP address of the
regression agent.
[0022] 2. Queue Size
[0023] The traffic load indicates a buffer size of a regression
agent. When the buffer size of the regression agent is lower than a
threshold, the buffer size is considered as "LIGHT".
[0024] 3. Registered Mobile Node Number at Regression Agent
[0025] The regression agent should monitor the queue size and the
registered mobile node number. Each regression agent periodically
broadcasts traffic load broadcast information to all the other
regression agents in the regression network. The traffic load
broadcast information has the same regions as those in the traffic
load table.
[0026] According to the IPv6 protocol, this broadcast information
is based on unsolicited router broadcast information in the IETF
neighbor discovery protocol. By setting a new option and a traffic
load, the new option can be embedded into the optional regions of
the unsolicited router broadcast information. This option region is
as follows.
[0027] Queue Size (1 byte): a coarse parameter for the queue size
in the router TLT.
[0028] Registered mobile node number (1 byte): If more than 256
mobile nodes are registered, the region will be a coarse parameter
in the router TLT.
[0029] The unsolicited router broadcast information should be
broadcasted based on a time interval parameter [MinRtrAdvInterval]
defined by IETF RFC 2461. In order to update traffic information in
time, the unsolicited router broadcast information with traffic
load information should be sent within a time interval
[MinRtrAdvInterval, MinRtrAdvInterval+IntervalTLTE-
xtetension].
[0030] Here, IntervalTLTExtetension=2*MinRtrAdvInterval.
[0031] Once the traffic load broadcast information is received from
other regression agent, the regression agent should record the
information into the traffic load table. The regression agent sorts
traffic load information in the traffic load table in a descendent
order. The regression agent table is mainly sorted in a descendent
order except that the traffic load is "LIGHT". For the "LIGHT"
regression agent, the traffic load table is sorted in the
descendent order according to the registered mobile node
number.
[0032] In the present invention, the queue size is used to
determine and reset the regression agent. The registered mobile
node number can prevent the traffic load bottleneck from
occurrence.
[0033] FIG. 4 is a flow chart of a load balance method for multiple
regression home agents according to the present invention. This
method can determine whether or not a new regression agent should
be selected to balance the load.
[0034] The load balance method for multiple regression home agents
according to the present invention will be described in detail
below. Namely, how to perform a load balance among the multiple
regression home agents according to the mobile IPv6 network having
multiple distributed regression home agents will be described.
[0035] In the load balance method for multiple regression home
agents according to the present invention, it mainly solves an
issue of load balance and distribution among the multiple
regression home agents. This method considers how to solve and
prevent the traffic bottleneck from occurrence by considering
tunnel traffic information and registered mobile node number
information at each regression agent. The method proposed by the
present invention can be implemented by embedding DHAAD defined by
the mobile IPv6 standard, and can prevent the traffic load
bottleneck from occurring in advance.
[0036] Since the multiple regression home agents in the mobile IPv6
network having multiple distributed regression home agents
according to the present invention are arranged in a distributed
manner, all of the regression agents can determine whether or not a
handoff occurs. In the current technology, only a central dispatch
system can determine whether or not a handoff can be performed.
Therefore, the central dispatch system is not suitable for the
regression agent. Since the central dispatch system needs to handle
information of all the mobile nodes, it might become a traffic
bottleneck as the mobile node number increases greatly.
[0037] In the mobile IPv6 network having multiple distributed
regression home agents according to the present invention, the
regression network is composed of a number of regression agents of
the mobile IPv6 and a number of mobile nodes. When the mobile node
stays at the regression network, the regression agent does not
execute any task of the regression agent. When initializing the
regression network, the registered mobile nodes of the regression
agents in the regression network can be evenly disposed or unevenly
disposed. Whether the regression agents are evenly disposed or not
will not affect an initial traffic load and the ability of the
above-mentioned load balance method.
[0038] In each regression agent, a timer and a binding update
buffer region are combined. When registering a mobile node, the
timer starts clocking and a binding time of the current
registration is stored into the binding update buffer region. When
the timer exceeds the binding time, i.e., when the timer of the
corresponding mobile node is time-out, the mobile node performs an
reassignment of the regression agent. Namely, the regression agent
selects a new regression agent from the traffic load table. If a
new regression agent is assigned to the aforementioned time-out
mobile node, the regression agent actively sends ICMP response
information packet to the mobile node and the mobile node does not
require sending ICMP request information. The aforementioned ICMP
response information packet is different from a standard ICMP
response datagram. The ICMP response information packet can have
only the newly selected regression agent, not including the
regression agent table, so that the data transmission amount in the
network is reduced. Upon receiving the ICMP information, the
aforementioned time-out mobile node compares the received
regression agent and its old regression agent. If the regression
agent indicated by the above ICMP response information packet is
different from the old regression agent, the mobile node will
modify its regression agent and send binding update request
information to the new regression agent at the same time. By using
ICMP information defined by the DHAAD, the present invention can be
implemented together with the IETF mobile IPv6 standard without any
change of the protocol.
[0039] For the mobile node, the frequency of modifying the new
regression agent is a tradeoff between the handoff of the
regression agents and the load balance performance. The regression
agent should not frequently select a new regression agent for the
registered mobile node. Because the handoff of the regression agent
will bring an additional traffic control and delays for the normal
traffic communication of the mobile node, only a very busy mobile
node or a potentially very busy mobile node processes the handoff
of the regression agent.
[0040] If a new regression agent is to be selected, this regression
agent should be the most released regression agent in the traffic
load table. Two regions in the traffic load table can be used to
perform a selection algorithm. One is the queue size, used to
indicate the current traffic load; and the other one is the
registered mobile node number, used to indicate a potential traffic
load in the future. The regression agent should be prevented from
having too many registered mobile node numbers, so that the future
tunnel traffic load bottleneck can be prevented from being
formed.
[0041] Referring to FIG. 4, the load balance method for multiple
regression home agents according to the present invention is
implemented as follows.
[0042] Once a timer corresponding to a certain mobile node exceeds
the binding time, the regression agent corresponding to the mobile
node processes operations in the steps of:
[0043] (S1) determining whether a load is larger than a threshold
or not, and executing Step S2 if the determined result is "YES" and
executing Step S3 if the determined result is "NO";
[0044] (S2) determining whether there is a "LIGHT" regression agent
or not, and executing Step S4 if the determined result is "YES" and
executing Step S5 if the determined result is "NO";
[0045] (S3) determining whether the registered mobile node number
in all "LIGHT" regression agents is top 10% or not, and executing
Step S8 if the determined result is "YES" and executing Step S7 if
the determined result is "NO";
[0046] (S4) randomly selecting one of the "LIGHT" regression agents
and returning;
[0047] (S5) determining whether the registered mobile node number
in all non-"LIGHT" regression agents is top 10% or not, and
executing Step S6 if the determined result is "YES" and executing
Step S7 if the determined result is "NO";
[0048] (S6) randomly selecting one of bottom 10% regression agents
in the non-"LIGHT" regression agents and returning;
[0049] (S7) performing no handoff operation of the regression agent
and returning; and
[0050] (S8) randomly selecting one of bottom 10% regression agents
in all the "LIGHT" regression agents and returning.
[0051] The above description describes the mobile IPv6 network
having multiple distributed regression home agents and the load
balance method for the multiple regression home agents. In the
reselection algorithm of the regression agent, only the most busy
regression agent can select a new regression agent for its
registered mobile nodes. Therefore, the reassignment for a new
regression agent does not take place frequently. When the mobile
node moves from one network to another network, in the IETF mobile
IPv6, the mobile node asks the regression agent to work for its
tunnel data traffic before the communication node binding
registration. Therefore, a regression agent having many registered
nodes may have a large amount of triangle router tunnel data. The
method of the present invention can perform a reselection operation
of the regression agent under the condition that a large amount of
traffic is crowded at the regression agent, so that the phenomenon
of traffic load bottleneck in the feature can be prevented in
advance.
[0052] The simulation result of the present invention shows that
the present invention can reduce the traffic delays significantly
and the buffer requirement when the triangle router tunnel
transmits data. FIG. 5 shows the queue size of the process queue at
each regression agent with and without the traffic load balance
method. The result shows the present invention can use multiple
regression agents to share the traffic loads according to the queue
size and the registered mobile node number when the regression
agent reaches a saturated traffic situation.
* * * * *